Experiments and Modeling for Infrastructure Data-Derived Fuel Economy and Safety Improvements

Connected and autonomous vehicles (CAV) are an important means by which the US can improve the safety, environmental compatibility, economics, and equity of personal transportation. This research seeks to synthesize both rich vehicle-level datasets derived from experiments with CAV sensors and systems and the state of the art transportation-system level datasets to compose second-by-second vehicle-level Lagrangian predictions of vehicle velocity trajectories, applicable to CAVs. We will seek to understand the role of advanced traffic management systems (ATMS) (and other infrastructure) sensors, information, and infrastructure in advancing the safety and environmental benefits of CAVs.


  • English


  • Status: Active
  • Funding: $120000
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Mountain-Plains Consortium

    North Dakota State University
    Fargo, ND  United States  58108
  • Project Managers:

    Tolliver, Denver

  • Performing Organizations:

    Colorado State University

    Dept. of Mechanical Engineering
    Fort Collins, CO  United States  80523
  • Principal Investigators:

    Bradley, Thomas

  • Start Date: 20180627
  • Expected Completion Date: 20240731
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program
  • Source Data: MPC-570

Subject/Index Terms

Filing Info

  • Accession Number: 01674929
  • Record Type: Research project
  • Source Agency: Mountain-Plains Consortium
  • Contract Numbers: 69A3551747108
  • Files: UTC, RIP
  • Created Date: Jul 10 2018 6:37PM